Dynamic memory model based optimization of scalar and vector quantizer for fast image encoding

Author

Cheung, Gene ; McCanne, Steven

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA

Volume

3

fYear

2000

fDate

2000

Firstpage

106

Abstract

The rapid progress of computers and today´s heterogeneous computing environment means computation-intensive signal processing algorithms must be optimized for performance in a machine dependent fashion. We present formal machine-dependent optimizations of scalar and vector quantizer encoders. Using a dynamic memory model, the optimal computation-memory tradeoff is exploited to minimize the encoding time. Experiments show marked improvements over existing techniques

Keywords

data compression; image coding; optimisation; vector quantisation; dynamic memory model based optimization; encoding time minimisation; fast image encoding; formal machine-dependent optimizations; heterogeneous computing environment; optimal computation-memory tradeoff; scalar quantizer encoder; signal processing algorithms; vector quantizer encoder; Algorithm design and analysis; Computational modeling; Costs; Encoding; High level languages; Image coding; Information retrieval; Pervasive computing; Quantization; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2000. Proceedings. 2000 International Conference on

Conference_Location

Vancouver, BC

ISSN

1522-4880

Print_ISBN

0-7803-6297-7

Type

conf

DOI

10.1109/ICIP.2000.899306

Filename

899306